Careers

The Selling Partner Experience (SPX) organization strives to make Amazon the best place for Selling Partners to do business. The SPX AI Lab team is building the AI capabilities powering the Selling Assistant, Amazon's conversational assistant experience for Selling Partners. The Selling Assistant is a trusted partner and a seasoned advisor that’s always available to enable our partners to thrive in Amazon’s stores. It takes away the cognitive load of selling on Amazon by providing a single interface to handle a diverse set of selling needs. The assistant always stays by the seller's side, talks to them in their language, enables them to capitalize on opportunities, and helps them accomplish their business goals with ease. It is powered by the latest advances in Generative AI, going beyond a typical chatbot to provide an intuitive, intelligent, agentic and personalized experience to sellers running real businesses, large and small. Do you want to join an innovative group of scientists, engineers, and product managers who use advanced analytical, statistical, and machine learning techniques to help Amazon create a delightful Selling Partner experience? Are you excited about uncovering insights from massive-scale data, measuring the impact of AI-driven features, and shaping product strategy through rigorous analysis? Do you want to be part of one of Amazon’s most strategic initiatives to understand and improve seller experience? If yes, the SPX AI Lab may be the perfect fit for you. Key job responsibilities -- Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience -- Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience. -- Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods). -- Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring. -- Apply NLP and statistical modeling techniques—including topic modeling, clustering, semantic similarity, and classification—to uncover insights from unstructured seller interactions, feedback, and content. -- Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations. -- Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams. -- Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement. -- Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI. About the team SPX AI Lab is a growing team of scientists driving the research and development of the next generation of GenAI experiences that empower Amazon's Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. We strive to radically simplify the seller experience, lowering the cognitive burden of selling on Amazon by making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon’s policies and taking actions to grow their business.

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you. Major responsibilities - Use machine learning and analytical techniques to create scalable solutions for business problems - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes - Design, development, evaluate and deploy innovative and highly scalable models for predictive learning - Research and implement novel machine learning and statistical approaches - Work closely with software engineering teams to drive real-time model implementations and new feature creations - Work closely with business owners and operations staff to optimize various business operations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Mentor other scientists and engineers in the use of ML techniques A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the International Emerging Stores organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team Central Machine Learning team works closely with the IES business and engineering teams in building ML solutions that create an impact for Emerging Marketplaces. This is a great opportunity to leverage your machine learning and data mining skills to create a direct impact on millions of consumers and end users.

Amazon is looking for creative Applied Scientists to tackle some of the most interesting problems in Artificial Intelligence (AI), natural language processing (NLP), knowledge graph curation, search, recommendation and related areas with our Amazon Books team. At Amazon Books we believe that reading is essential for a healthy society. As such, we aim to inspire readers by making it easy to read more and get more out of reading. We do this by creating an unmatched book discovery experience for our customers worldwide. We enable customers to discover new books, authors and genres through smart search tools, intelligent interactions and sophisticated recommendations, and we need your help to keep innovating in this space. If you are looking for an opportunity to solve deep technical problems and build innovative solutions in a fast-paced environment working within a smart and passionate team, this might be the role for you. You will develop and implement novel algorithms, agentic systems and modeling techniques to advance the state-of-the-art in technology areas at the intersection of AI, LLMs, NLP, search, and deep learning. You will innovate at scale, help move the needle for research in these exciting areas and build state-of-the-art technologies that enable delightful experiences for hundreds of millions of people. Key job responsibilities In this role you will: - Work collaboratively with other scientists and developers to design and implement scalable and reliable pipelines for ensuring our vast knowledge base of books meets the highest levels of accuracy and is aligned with how customers think about books; - set the scientific roadmap needed to sustain state-of-the-art quality and efficiency. Stay up-to-date with the latest technologies and adopt the most appropriate long-term solution to a variety of use cases. - set the standard for science rigor and quality, deal with ambiguity and competing objectives, and mentor other members to achieve their career growth potential. - Drive scalable solutions: from understanding the customer and business needs, to prototyping, production testing and through engineering directly to production. A day in the life Day-to-day work varies, but on a typical day you will: - run (or supervise) experiments. Depending on the stage or project, this may involve designing the experiments, collecting data, training models, prompt/spec engineering/optimization, error analysis, online system analysis, etc. - drive decisions by interpreting and communicating experimental results with stakeholders (managers, subject matter experts, other scientists, and engineers) and seeking/listening to their feedback. - strategic thinking: review results, identify trends and what step-changes are needed. You'll contribute to regular meetings, activities and conferences with the wider science team, organization as well as internal and external communities. About the team The team consists of a collaborative group of scientists, product leaders, and dedicated engineering teams. Our aim is to maintain the world’s most accurate and descriptive set of books metadata, where every title in our catalog is uniquely characterized via a set of high-quality, concise attributes. We believe this is a foundational capacity for any bookstore. We work with sister teams to leverage our systems to drive a diverse array of customer experiences, owned both by ourselves and others, that enable customers to easily identify their ideal next read.

The Amazon Center for Quantum Computing in Pasadena, CA, is looking to hire a Fabrication R&D Scientist with experience in semiconductor process development who will aid in Amazon’s effort to bring cloud quantum computing services to its worldwide customer base. You will join a multi-disciplinary team of scientists, and hardware and software engineers working at the forefront of quantum computing. Through your work inside and outside of the cleanroom environment in the fabrication research and development group, you will solve problems related to developing next-generation quantum processors. Candidates must have a demonstrated background in sound scientific and engineering principles, and must have excellent data analysis, bias for action, problem solving, and communication skills, and be highly motivated and curious to research and learn new technical topics as needed. As a Fab R&D scientist you will be expected to work on new ideas and stay abreast of novel approaches in fabricating and packaging superconducting quantum processors. Working effectively within a team environment is critical. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Work/Life Balance Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Export Control Requirement Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility. Key job responsibilities Responsibilities include developing and optimizing processes to fabricate high-coherence superconducting qubits; developing advanced 3DI interconnect and routing technologies for integrating superconducting quantum technologies; analyzing inline metrology and electrical test data; developing and maintaining integration documentation, design rules, and standard operating procedures; interacting with project leads to provide feedback that continuously improves different processes; staying updated with the latest advancements and industry trends in process integration and apply knowledge to improve processes and drive innovation providing technical guidance and support to junior colleagues, fostering a collaborative and knowledge-sharing work environment. A day in the life The candidate will develop novel technologies using micro-/nano-fabrication techniques inside the cleanroom (independently or in collaboration with other scientists, engineers, and technicians) for next-generation quantum computing. Outside the cleanroom, the candidate will plan experiments, analyze data, and conceive future innovations.

Have you ever wondered how that Amazon box with the smile arrives so quickly, where it came from, and how much it cost Amazon to deliver? The WW Amazon Logistics, Business Analytics team manages the delivery of tens of millions of products every week to Amazon's customers, achieving on-time delivery in a cost-effective manner. We are seeking an enthusiastic, customer-obsessed Sr. Manager Research Science with strong analytical skills to join our team. This role is crucial in optimizing Amazon's vast delivery network and will have significant impact on the customer experience, particularly in the final phase of delivery. As a Sr. Manager Research Science, you will: 1. Address business challenges through building compelling cases and using data to influence change across the organization 2. Develop input and assumptions based on preexisting models to estimate costs and savings opportunities associated with varying levels of network growth and operations 3. Create metrics to measure business performance, identify root causes and trends, and prescribe action plans 4. Manage multiple high-impact projects simultaneously 5. Work with technology teams and product managers to develop new tools and systems supporting business growth 6. Communicate with and support various internal stakeholders and external audiences 7. Implement scheduling solutions, improve metrics, and develop scalable processes and tools The ideal candidate will have: - Extensive experience in operations research and data-driven decision making - Strong analytical and problem-solving skills - Robust program management and research science skills - Ability to work with a team and make independent decisions in ambiguous environments - Customer-obsessed mindset with a focus on improving the Amazon delivery experience This role offers the autonomy to think strategically and make data-driven decisions from day one. Join us in shaping the future of e-commerce delivery and addressing the core challenges in our world-class operations space! Key job responsibilities 1. Advanced Modeling and Algorithm Development: - Design and implement sophisticated machine learning models for logistics optimization - Develop complex time series forecasting algorithms for demand prediction and resource allocation 2. AI and Machine Learning Integration: - Architect and deploy AI-powered systems to enhance decision-making in logistics operations - Implement deep learning techniques for image recognition in package sorting and handling - Develop reinforcement learning algorithms for adaptive scheduling and resource management 3. Big Data Analytics and Processing: - Design and implement distributed computing solutions for processing massive logistics datasets - Utilize cloud computing platforms (e.g., AWS) for scalable data processing and analysis 4. AI-Driven Workflow Optimization: - Design and implement AI agents for autonomous decision-making in logistics processes - Create machine learning models for customer behavior analysis and personalized delivery options 5. Software Development and System Architecture: - Write efficient, scalable code in languages such as Python, Java, or C++ - Develop and maintain complex software systems for logistics optimization - Stay at the forefront of AI and ML research - Publish research findings in top-tier conferences and journals About the team We are Amazon's Last Mile Science and Analytics team, dedicated to improving e-commerce delivery. We work to optimize our vast network, forecast demand using machine learning, and enhance route efficiency. Our efforts focus on developing innovative delivery methods, applying AI to solve complex problems, and conducting geospatial analysis. We create simulations to refine processes and plan capacity effectively. Operating globally, we strive to develop adaptable solutions for diverse markets. We aim to advance logistics science, continually improving speed, efficiency, and customer satisfaction, in support of Amazon's mission to be Earth's most customer-centric company.

Lead ML teams building large-scale forecasting and optimization systems that power Amazon’s global transportation network and directly impact customer experience and cost. As an Sr Applied Scientist, you will set scientific direction, mentor applied scientists, and partner with engineering and product leaders to deliver production-grade ML solutions at massive scale. Key job responsibilities 1. Lead and grow a high-performing team of Applied Scientists, providing technical guidance, mentorship, and career development. 2. Define and own the scientific vision and roadmap for ML solutions powering large-scale transportation planning and execution. 3. Guide model and system design across a range of techniques, including tree-based models, deep learning (LSTMs, transformers), LLMs, and reinforcement learning. 4. Ensure models are production-ready, scalable, and robust through close partnership with stakeholders. Partner with Product, Operations, and Engineering leaders to enable proactive decision-making and corrective actions. 5. Own end-to-end business metrics, directly influencing customer experience, cost optimization, and network reliability. 6. Help contribute to the broader ML community through publications, conference submissions, and internal knowledge sharing. A day in the life Your day includes reviewing model performance and business metrics, guiding technical design and experimentation, mentoring scientists, and driving roadmap execution. You’ll balance near-term delivery with long-term innovation while ensuring solutions are robust, interpretable, and scalable. Ultimately, your work helps improve delivery reliability, reduce costs, and enhance the customer experience at massive scale.

Who are we? Do you want to build Amazon's next $100B business? We're not just joining the shipping industry—we're transforming how billions of packages move across the world every year. Through evolving Amazon's controlled, predictable fulfillment network into a dynamic, adaptive shipping powerhouse we are building an intelligent system that optimizes in real-time to deliver on the promises businesses make to their customers. Our mission goes beyond moving boxes—we're spinning a flywheel where every new package makes our network stronger, faster, and more efficient. As we increase density and scale, we're revolutionizing shipping for businesses while simultaneously strengthening Amazon's own delivery capabilities, driving down costs and increasing speed for our entire ecosystem. What will you do? Amazon shipping is seeking a Senior Data Scientist with strong pricing and machine learning skills to work in an embedded team, partnering closely with commercial, product and tech. This person will be responsible for developing demand prediction models for Amazon shipping’s spot pricing system. As a Senior Data Scientist, you will be part of a science team responsible for improving price discovery across Amazon shipping, measuring the impact of model implementation, and defining a roadmap for improvements and expansion of the models into new unique use cases. This person will be collaborating closely with business and software teams to research, innovate, and solve high impact economics problems facing the worldwide Amazon shipping business. Who are you? The ideal candidate is analytical, resourceful, curious and team oriented, with clear communication skills and the ability to build strong relationships with key stakeholders. You should be a strong owner, are right a lot, and have a proven track record of taking on end-to-end ownership of and successfully delivering complex projects in a fast-paced and dynamic business environment. As this position involves regular interaction with senior leadership (director+), you need to be comfortable communicating at that level while also working directly with various functional teams. Key job responsibilities * Combine ML methodologies with fundamental economics principles to create new pricing algorithms. * Automate price exploration through automated experimentation methodologies, for example using multi-armed bandit strategies. * Partner with other scientists to dynamically predict prices to maximize capacity utilization. * Collaborate with product managers, data scientists, and software developers to incorporate models into production processes and influence senior leaders. * Educate non-technical business leaders on complex modeling concepts, and explain modeling results, implications, and performance in an accessible manner. * Independently identify and pursue new opportunities to leverage economic insights * Opportunity to expand into other domains such as causal analytics, optimization and simulation. About the team Amazon Shipping's pricing team empowers our global business to find strategic harmony between growth and profit tradeoffs, while seeking long term customer value and financial viability. Our people and systems help identify and drive synergy between demand, operational, and economic planning. The breadth of our problems range from CEO-level strategic support to in-depth mathematical experimentation and optimization. Excited by the intersection of data and large scale strategic decision-making? This is the team for you!

At Amazon, we strive every day to be Earth’s most customer-centric company. Selling Partner Support Engagement (SPSE) Science delivers on this by building AI-enhanced experiences that provide world class support to our global network of selling partners. We are building applications at the forefront of GenAI applications, tackling the challenges caused by the volume, diversity, and complexity of our selling partner's needs. Do you want to join a team of scientists with critical problem solving skills who are innovating on behalf of our customers using natural language processing and generative AI? Are you interested in helping us redefine what world class support can be in an age of automation and AI, while prizing human empathy and ingenuity? Are you excited by the prospect of your solutions resulting in large-scale impact while getting a chance to research at the forefront of AI innovation? The SPSE Science Team is looking for a Senior Applied Scientist to build machine learning and GenAI solutions (agentic frameworks) that help us understand and solve our sellers' most challenging problems. We need to better understand our Sellers and the problems they face, to augment our human workforce with smarter tools and to automatically diagnose and resolve issues. In this role, you will have ownership of the end-to-end development of solutions to complex problems and you will play an integral role in strategic decision-making. You will also work closely with engineers, operations teams and product owners to build ML pipelines, platforms and solutions that solve problems of defect detection, automation, and workforce optimization. Key job responsibilities Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of tools that empower Amazon's Selling Partners and Support Associates to succeed. Design, develop and deploy models that either interact with end users or automate entire workflows. Work closely with teams of scientists and software engineers to drive online model implementations with impactful features through A/B testing. Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation. Research and implement novel machine learning approaches. Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment. Raise the bar for ML design and execution for the scientists on the team. Assist in hiring the best talent on the team. About the team Selling Partner Support Engagement Science (Titans Science) is a growing team of scientists engaged in the research and development of the next generation of ML-driven technology to empower Amazon's Selling Partners to succeed. We strive to radically simplify the seller experience, making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon’s policies and taking actions to grow their business. Scientists on the team get an opportunity to learn the state of the art end-to-end ML tooling and infrastructure offered through AWS and other open source technology stacks. The complexity of our work also give scientists an opportunity to successfully publish research in leading journals and conferences. We value diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. Additionally, the team fosters an inclusive and learning culture, inspiring us to embrace our uniqueness. We highly value individual growth; you will also find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON ADVERTISING LLC Offered Position: Data Scientist II Job Location: New York, New York Job Number: AMZ9658237 Position Responsibilities: Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. 40 hours / week, 8:00am-5:00pm, Salary Range $169,541/year to $207,500/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000

The Amazon Search team creates customer-focused search solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, Amazon Product Search services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. Our Search Relevance team works to maximize the quality and effectiveness of the search experience for visitors to Amazon websites worldwide. The Search Relevance team focuses on several technical areas for improving search quality. In this role, you will invent universally applicable signals and algorithms for training machine-learned ranking models. The relevance improvements you make will help millions of customers discover the products they want from a catalog containing millions of products. You will work on problems such as predicting the popularity of new products, developing new ranking features and algorithms that capture unique characteristics, and analyzing the differences in behavior of different categories of customers. The work will span the whole development pipeline, including data analysis, prototyping, A/B testing, and creating production-level components. Joining this team, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon.com (AMZN), one of the world’s leading Internet companies. We provide a highly customer-centric, team-oriented environment in our offices located in Palo Alto, California. Please visit https://www.amazon.science for more information